datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
PubChem-124M-SMILES-SELFIES-InChI-IUPAC
PubChem-124M-Canonicalized-SELFIES-InChI-IUPAC
Dataset Summary
This dataset contains ~124 million chemical structures sourced from PubChem (as of Jan 2026), processed into a clean, machine-learning-ready Parquet format.
Unlike raw XML/JSON dumps or standard CSVs, this dataset provides a unified, tabular structure that joins multiple chemical identifiers and descriptors into a single sharded resource:
SMILES: Raw and RDKit-Canonicalized.
SELFIES: Pre-computed 100% robust… See the full description on the dataset page: https://huggingface.co/datasets/hheiden/PubChem-124M-SMILES-SELFIES-InChI-IUPAC.PubChem-124M-SMILES-SELFIES-InChI-IUPAC
PubChem-124M-Canonicalized-SELFIES-InChI-IUPAC
Dataset Summary
This dataset contains ~124 million chemical structures sourced from PubChem (as of Jan 2026), processed into a clean, machine-learning-ready Parquet format.
Unlike raw XML/JSON dumps or standard CSVs, this dataset provides a unified, tabular structure that joins multiple chemical identifiers and descriptors into a single sharded resource:
SMILES: Raw and RDKit-Canonicalized.
SELFIES: Pre-computed… See the full description on the dataset page: https://huggingface.co/datasets/Bilsteen/PubChem-124M-SMILES-SELFIES-InChI-IUPAC.PubChem-124M-SMILES-SELFIES-InChI-IUPAC
PubChem-124M-Canonicalized-SELFIES-InChI-IUPAC
Dataset Summary
This dataset contains ~124 million chemical structures sourced from PubChem (as of Jan 2026), processed into a clean, machine-learning-ready Parquet format.
Unlike raw XML/JSON dumps or standard CSVs, this dataset provides a unified, tabular structure that joins multiple chemical identifiers and descriptors into a single sharded resource:
SMILES: Raw and RDKit-Canonicalized.
SELFIES: Pre-computed 100% robust… See the full description on the dataset page: https://huggingface.co/datasets/th-laurel/PubChem-124M-SMILES-SELFIES-InChI-IUPAC.chemq3-molsim-sft-smiles
ECFP4 Molecular Pairs Dataset
A dataset of molecular pairs with ECFP4 Dice similarity scores uniformly sampled across a target range, using FAISS for efficient similarity search.
This pipeline intended to generate a high-quality dataset of molecular pairs for similarity-based learning, balancing chemical diversity, computational efficiency, and target similarity distribution.
Specially designed to retain only pairs with 0.5 ≤ Dice(MACCS) ≤ 0.95—a targeted range for supervised… See the full description on the dataset page: https://huggingface.co/datasets/gbyuvd/chemq3-molsim-sft-smiles.bioactives-naturals-smiles-molgen
Valid Bioactives and Natural Product SMILES
~2.7M valid SMILES built and curated from ChemBL34 (Zdrazil et al. 2023), COCONUTDB (Sorokina et al. 2021), and Supernatural3 (Gallo et al. 2023) dataset.
Curated by: gbyuvd
References
BibTeX
COCONUTDB
@article{sorokina2021coconut,
title={COCONUT online: Collection of Open Natural Products database},
author={Sorokina, Maria and Merseburger, Peter and Rajan, Kohulan and Yirik, Mehmet Aziz and Steinbeck… See the full description on the dataset page: https://huggingface.co/datasets/gbyuvd/bioactives-naturals-smiles-molgen.